Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/207665
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dc.contributor.authorWeize Zhangen_US
dc.contributor.authorJuntian Quen_US
dc.contributor.authorXuping Zhangen_US
dc.contributor.authorXinyu Liuen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:57:07Z-
dc.date.available2020-04-06T07:57:07Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TMECH.2017.2721159en_US
dc.identifier.urihttp://localhost/handle/Hannan/207665-
dc.description.abstractMany micromanipulation systems employ sensorless actuators and possess unknown modeling errors, feedback measurement noises, and time delays. Conventional model-based control schemes ignore some of these uncertainties, and thus sacrifice the control system performance. This paper presents a new model compensation-prediction scheme for micromanipulation systems that can be described by two-dimensional state-space models, estimate the unknown modeling errors from noisy single feedback measurement, and predict and compensate the system time delay. This approach combines two modeling errors into a single equivalent modeling error through mathematical transformation, and estimates the combined term using a noise-insensitive extended high-gain observer. After removing the unknown term, the system is then transformed into a time-invariant form, and a Smith predictor is implemented to predict and compensate the time delay. The effectiveness of the proposed compensation-prediction scheme is demonstrated by both numerical simulations and experiments on two typical micromanipulation systems, namely a robotic biosample stimulator and a material characterization microgripper. The results show that this method can significantly improve the control performance of a conventional proportional-integral-derivative controller, by simultaneously reducing the settling time and overshoot of the micromanipulation systems.en_US
dc.format.extent1973,en_US
dc.format.extent1982en_US
dc.publisherIEEEen_US
dc.relation.haspart7961243.pdfen_US
dc.titleA Model Compensation-Prediction Scheme for Control of Micromanipulation Systems With a Single Feedback Loopen_US
dc.typeArticleen_US
dc.journal.volume22en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
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7961243.pdf710.37 kBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWeize Zhangen_US
dc.contributor.authorJuntian Quen_US
dc.contributor.authorXuping Zhangen_US
dc.contributor.authorXinyu Liuen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:57:07Z-
dc.date.available2020-04-06T07:57:07Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TMECH.2017.2721159en_US
dc.identifier.urihttp://localhost/handle/Hannan/207665-
dc.description.abstractMany micromanipulation systems employ sensorless actuators and possess unknown modeling errors, feedback measurement noises, and time delays. Conventional model-based control schemes ignore some of these uncertainties, and thus sacrifice the control system performance. This paper presents a new model compensation-prediction scheme for micromanipulation systems that can be described by two-dimensional state-space models, estimate the unknown modeling errors from noisy single feedback measurement, and predict and compensate the system time delay. This approach combines two modeling errors into a single equivalent modeling error through mathematical transformation, and estimates the combined term using a noise-insensitive extended high-gain observer. After removing the unknown term, the system is then transformed into a time-invariant form, and a Smith predictor is implemented to predict and compensate the time delay. The effectiveness of the proposed compensation-prediction scheme is demonstrated by both numerical simulations and experiments on two typical micromanipulation systems, namely a robotic biosample stimulator and a material characterization microgripper. The results show that this method can significantly improve the control performance of a conventional proportional-integral-derivative controller, by simultaneously reducing the settling time and overshoot of the micromanipulation systems.en_US
dc.format.extent1973,en_US
dc.format.extent1982en_US
dc.publisherIEEEen_US
dc.relation.haspart7961243.pdfen_US
dc.titleA Model Compensation-Prediction Scheme for Control of Micromanipulation Systems With a Single Feedback Loopen_US
dc.typeArticleen_US
dc.journal.volume22en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7961243.pdf710.37 kBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorWeize Zhangen_US
dc.contributor.authorJuntian Quen_US
dc.contributor.authorXuping Zhangen_US
dc.contributor.authorXinyu Liuen_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:57:07Z-
dc.date.available2020-04-06T07:57:07Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TMECH.2017.2721159en_US
dc.identifier.urihttp://localhost/handle/Hannan/207665-
dc.description.abstractMany micromanipulation systems employ sensorless actuators and possess unknown modeling errors, feedback measurement noises, and time delays. Conventional model-based control schemes ignore some of these uncertainties, and thus sacrifice the control system performance. This paper presents a new model compensation-prediction scheme for micromanipulation systems that can be described by two-dimensional state-space models, estimate the unknown modeling errors from noisy single feedback measurement, and predict and compensate the system time delay. This approach combines two modeling errors into a single equivalent modeling error through mathematical transformation, and estimates the combined term using a noise-insensitive extended high-gain observer. After removing the unknown term, the system is then transformed into a time-invariant form, and a Smith predictor is implemented to predict and compensate the time delay. The effectiveness of the proposed compensation-prediction scheme is demonstrated by both numerical simulations and experiments on two typical micromanipulation systems, namely a robotic biosample stimulator and a material characterization microgripper. The results show that this method can significantly improve the control performance of a conventional proportional-integral-derivative controller, by simultaneously reducing the settling time and overshoot of the micromanipulation systems.en_US
dc.format.extent1973,en_US
dc.format.extent1982en_US
dc.publisherIEEEen_US
dc.relation.haspart7961243.pdfen_US
dc.titleA Model Compensation-Prediction Scheme for Control of Micromanipulation Systems With a Single Feedback Loopen_US
dc.typeArticleen_US
dc.journal.volume22en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7961243.pdf710.37 kBAdobe PDF